29 citations · 76 across the 11 of their papers we have counts for
11 papers
Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild
Mao Zheng, Zheng Li, Tao Chen +10
Hy-MT2 is a family of fast-thinking multilingual translation models designed for complex real-world scenarios. It includes three model sizes: 1.8B, 7B, and 30B-A3B (MoE), all of wh…
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning
Hoifung Poon, Hai Wang, Hunter Lang
Deep learning has proven effective for various application tasks, but its applicability is limited by the reliance on annotated examples. Self-supervised learning has emerged as a…
Knowledge Efficient Deep Learning for Natural Language Processing
Hai Wang
Deep learning has become the workhorse for a wide range of natural language processing applications. But much of the success of deep learning relies on annotated examples. Annotati…
On-The-Fly Information Retrieval Augmentation for Language Models
Hai Wang, David McAllester
Here we experiment with the use of information retrieval as an augmentation for pre-trained language models. The text corpus used in information retrieval can be viewed as form of…
Improving Pre-Trained Multilingual Models with Vocabulary Expansion
Hai Wang, Dian Yu, Kai Sun +2
Recently, pre-trained language models have achieved remarkable success in a broad range of natural language processing tasks. However, in multilingual setting, it is extremely reso…
Evidence Sentence Extraction for Machine Reading Comprehension
Hai Wang, Dian Yu, Kai Sun +4
Remarkable success has been achieved in the last few years on some limited machine reading comprehension (MRC) tasks. However, it is still difficult to interpret the predictions of…
Learning to Globally Edit Images with Textual Description
Hai Wang, Jason D. Williams, SingBing Kang
We show how we can globally edit images using textual instructions: given a source image and a textual instruction for the edit, generate a new image transformed under this instruc…
Deep Probabilistic Logic: A Unifying Framework for Indirect Supervision
Hai Wang, Hoifung Poon
Deep learning has emerged as a versatile tool for a wide range of NLP tasks, due to its superior capacity in representation learning. But its applicability is limited by the relian…
Emergent Predication Structure in Hidden State Vectors of Neural Readers
Hai Wang, Takeshi Onishi, Kevin Gimpel +1
A significant number of neural architectures for reading comprehension have recently been developed and evaluated on large cloze-style datasets. We present experiments supporting t…
Broad Context Language Modeling as Reading Comprehension
Zewei Chu, Hai Wang, Kevin Gimpel +1
Progress in text understanding has been driven by large datasets that test particular capabilities, like recent datasets for reading comprehension (Hermann et al., 2015). We focus…
Who did What: A Large-Scale Person-Centered Cloze Dataset
Takeshi Onishi, Hai Wang, Mohit Bansal +2
We have constructed a new "Who-did-What" dataset of over 200,000 fill-in-the-gap (cloze) multiple choice reading comprehension problems constructed from the LDC English Gigaword ne…